One step method of structure engineering porous graphitic carbon nitride for efficient visible-light photocatalytic reduction of Cr(Ⅵ)

Porous g-C3N4 nanosheets (PCN) were prepared by the nickel-assisted one-step thermal polymerization method.Hydrogen (H2) which was produced by the reaction between nickel (Ni) foam and ammonia (NH3) defined the structure and properties of PCN.During the formation of PCN,the participation of H2 not only enhanced the spacing between layers but also boosted the specific surface area that more active sites were exposed.Additionally,H2 promoted pores formation in the nanosheets,which was beneficial to the transfer of photons through lamellar structure and improved the absorption efficiency of visible light.Remarkably,the obtained PCN possessed better Cr(Ⅵ) photocatalytic reduction efficiency than pure g-C3N4.The reaction rate constant (k) of PCN (0.013 min-1) was approximately twice that of bare g-C3N4 (0.007 min-1).Furthermore,the effects of original pH and concentration of Cr(Ⅵ)-containing solution on removal efficiency of Cr(Ⅵ) were explored.A possible photocatalytic mechanism was proposed based on the experiments of radical scavengers and photoelectrochemical characterizations.     

Hydrogen Production from Catalytic Steam Reforming of Bio-Oils: A Critical Review

In the future, hydrogen will be an important energy carrier and industrial raw material. Catalytic steam reforming of bio-oils is a promising and economically viable technology for hydrogen production. However, during the reforming process, the catalysts are rapidly deactivated due to coke formation and sintering. Thus, maintaining the activity and stability of catalysts is the key issue in this process. Optimized operation conditions could extend the catalyst lifetime by affecting the coke morphology or promoting coke gasification. This article summarizes the recent developments in the field of catalytic steam reforming of bio-oils, focusing on the operation conditions, the properties of the catalysts, and the effects of the catalyst supports. The expected insights into the catalytic steam reforming of bio-oils will provide further guidance for hydrogen production from bio-oils.     

基于神经网络和遗传算法的锭子弹性管性能优化

为得到减振弹性管对下锭胆的支承弹性和锭子高速运动下的稳定性等性能的最优匹配效率,依据减振弹性管的等效抗弯刚度及底部等效刚度系数公式,利用MatLab数值分析软件构建弹性管抗弯刚度和底部挠度数学模型。首先,结合Isight优化软件基于径向基神经网络构建其近似模型,且使精度达到可接受水平,并以模型的关键结构参数弹性模量、螺距、槽宽、壁厚为设计变量,结合遗传算法对弹性管抗弯刚度和底部挠度进行多目标优化设计,得到Pareto最优解集和Pareto前沿图,确定出减振弹性管结构工艺参数的优化方案。通过对优化数据进行分析发现,该方案在保证减振弹性管弹性的同时,其底部振幅明显减弱。     

iRGD-reinforced,photo-transformable nanoclusters toward cooperative enhancement of intratumoral penetration and antitumor efficacy

Nano Research - Insufficient intratumoral penetration greatly hurdles the anticancer performance of nanomedicine. To realize highly efficient tumor penetration in a precisely and spatiotemporally...     

Reconstructing gene regulatory networks with a memetic-neural hybrid based on fuzzy cognitive maps

Reconstructing gene regulatory networks (GRNs) plays an important role in identifying the complicated regulatory relationships, uncovering regulatory patterns in cells, and gaining a systematic view for biological processes. In order to reconstruct large-scale GRNs accurately, in this paper, we first use fuzzy cognitive maps (FCMs), which are a kind of cognition fuzzy influence graphs based on fuzzy logic and neural networks, to model GRNs. Then, a novel hybrid method is proposed to reconstruct GRNs from time series expression profiles using memetic algorithm (MA) combined with neural network (NN), which is labeled as MANN_FCM-GRN. In MANN_FCM-GRN, the MA is used to determine regulatory connections in GRNs and the NN is used to determine the interaction strength of the regulatory connections. In the experiments, the performance of MANN_FCM-GRN is validated on both synthetic data and the benchmark dataset DREAM3 and DREAM4. The experimental results demonstrate the efficacy of MANN_FCM-GRN and show that MANN_FCM-GRN can reconstruct GRNs with high accuracy without expert knowledge. The comparison with existing algorithms also shows that MANN_FCM-GRN outperforms ant colony optimization, non-linear Hebbian learning, and real-coded genetic algorithms.

     

Chemotherapy response of pancreatic cancer by diffusion-weighted imaging (DWI) and intravoxel incoherent motion DWI (IVIM-DWI) in an orthotopic mouse model

Magnetic Resonance Materials in Physics, Biology and Medicine - To investigate the value of using diffusion-weighted imaging (DWI) and intravoxel incoherent motion DWI (IVIM-DWI) to assess the...     

亲子乐园空调送风方式的数值模拟研究

大型综合室内亲子乐园属于高大空间,设有游乐设施和游戏的特殊性使得对空间的舒适性要求一致,但是送风气流遇阻严重,室内存在较多气流死角,影响室内空气质量和儿童健康。因此其空调设计不仅需要考虑温度、风速的空间均匀度,还要考虑各点的空气龄和PMV-PPD指标。以天津某亲子乐园为研究对象,利用scSTREAM软件对适用于该房间的辐射供冷加新风、置换通风、混合通风三种空调方式的送风效果进行数值模拟分析,从流场的均匀性、人员的热舒适性等方面对模拟结果进行探讨,研究结果表明辐射供冷加新风方式的空间均匀性和PMV指标最佳,混合通风方式的空气龄最小。     

胡萝卜丁中维生素C在热风辅助射频干燥过程中降解的动力学模型

目的研究热风辅助射频(hot air-assisted radio frequency,HA-RF)干燥过程中维生素C随温度变化的降解动力学模型。方法在6.5 cm极板间距和60℃热风系统条件下进行HA-RF干燥,重点研究胡萝卜丁中维生素C在干燥过程中的降解动力学,包括脱氢抗坏血酸(dehydroascorbic acid,DHAA)和抗坏血酸(ascorbic acid,AA)。总维生素C含量采用2,4-硝基苯肼分光光度法测定,AA采用2,6-二氯吲哚酚滴定法测定。结果HA-RF干燥过程中维生素C的降解规律符合一级可逆模型,其降解活化能为40.54 kJ/mol。DHAA活化能为35.83 kJ/mol,表明DHAA的稳定性低于AA。结论本研究使用的干燥温度为62.5~77.5℃,较高的干燥温度下维生素C降解速率较高,较低处理温度下的降解过程具有更好的模型适应度(R2>0.98)。     

共享交通的时空轨迹检索与群体发现

为解决共享交通下的共乘用户群体发现效率低、准确率不高问题，依据R-树原理建立GeoOD-Tree索引，并在此基础上提出以最大化共乘率为目标的群体发现策略。首先，对原始时空轨迹数据进行特征提取与标定处理，挖掘有效出行起讫点（OD）轨迹；其次，针对用户起讫点轨迹的特征，建立GeoOD-Tree索引进行有效的存储管理；最后，给出以最大化共乘行程为目标的群体发现模型，并运用K最近邻（KNN）查询对搜索空间剪枝压缩，提高群体发现效率。采用西安市近12000辆出租车营运轨迹数据，选取动态时间规整（DTW）等典型算法与所提算法在查询效率与准确率上进行性能对比分析。与DTW算法相比，所提算法的准确率提高了10.12%，查询效率提高了约15倍。实验结果表明提出的群体发现策略能有效提高共乘用户群体发现的准确率和效率，可有效提升共乘出行方式的出行率。